1. Technical Field
The present invention relates generally to Internet searching, and more particularly to performing image searches over the Internet.
2. Related Art
Currently, text based search engines are normally used to find image content over the Internet. When using text words or descriptors correlated to image file names or Meta data to find images, it is difficult for a person who is not well versed in the search operation to get more focused and relevant search results. Too few words in the text search string lead to too many search results that are not of interest or relevant to the user. If the user tries to add more words into the search string, aiming to retrieve results of high relevance, there is a tendency that the search results getting more unfocussed. It is often the user's sole responsibility to construct an efficient search string using logical AND, OR, etc., operators which can help in retrieving more relevant image search results, and the crafting of a sufficient search string may take many tries or may be frustrated entirely in the end. For a novice user, without proper knowledge of using the search engine with such logical operators, it is simply impossible to perform efficient image searching on the Internet.
Presently, search engines do not differentiate between a text and image search. When the search results are presented to the user, contextually relevant images maybe presented deep inside a huge or long search result list of hundreds or thousands of images. Under such situations, the user may fail to identify the relevant images from the large search result list. This results in the user putting in a substantial amount of effort that will then become more frustrating for the user during the image search operation. Also, the isolated images that are also part of the text pages may further complicate the search operation adding confusion to the user.
The current image search engines do not help in screening the images presented to a user in response to a text search in a manner that is more contextual based on the use and environment where the picture resides. When the user enters a search string for searching images of his concern or perspective, it may so happen that lots of irrelevant images are also presented to him, based on the matching of a single word, not the more revealing surround content. Most of the times, the presented results will be so large that the user will fail to find the best image, or any relevant image at all. This aspect of lack of focus and context awareness of current image search engines is very serious in some situations. For example, when young children are looking for some images or pictures of their choice; it may so happen that they get adult image content or porn pictures accidentally mixed in with relevant pictures, a very serious drawback to be dealt with in the current image search algorithms.
Also, current search engines do not learn or understand what the user find relevant or what a user is looking for by the way of search interactions. As a consequence of this the search engine cannot track what the user is looking for during browsing a webpage. Thus, any event that happens during a search session such as user selecting a word, or phrase on the current webpage will not be considered by search engine to determine what images or content the user may be interesting in. Due to lack of this feature, further refinement of the search string during a search session is not possible. As a result of this the search results will often not be relevant to what the user is looking for.
There are some search engines which can query users only on a rudimentary basis for selecting the specific search domains or areas, but the search operations performed are limited to those domains only and the search engines do not address the problem of optimizing relevant search results to the user. Such search engines can not be considered as general purpose search engines, whose objective is to generate more focused search results from the web servers hosting images on the entire Internet, rather than a single or few limited domains of data/images. Basically, such domain-specific search engines are personalized search engines, which do search operations only within the domains of someone's local interest but not to a broad user's interest. Thus, search operations leading to limited domains will not suit the purpose of the users all the time, as what the user desires in terms of data and images maybe elsewhere in a different domain or search space.
Current search engines do not maintain a centralized database and update it periodically based on the routine search operations performed by the users to make the search results more focused or making them more contextual. Normally, visited sites through search operations are maintained in a search database, but such format of storage in a search database cannot be utilized for making the search operation more efficient during the subsequent search operations. Also, the mere link-based databases, which a search server maintains for normal Internet operation, can not help in refining image search queries for the user, thus a refined or augmented search string can not be derived for focused and efficient context-based image search operation. Therefore, a need exists for a more effective and efficient way of searching Internet-based image content.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of ordinary skill in the art through comparison of such systems with the present invention.